Port Congestion: Looking for Solutions

Looking for solutions, there are several tools that can be used to improve terminal management. First, efficient terminal management is more important than ever with the onset of containerization and post-Panamax ships creating more volume at the world’s ports. Terminal management has become a balancing act between production and efficiency. Some ports have already begun to employ different tools and technology to help them with the balancing act. Some of these tools include cargo tracking, customer service, predictive repairs, and terminal operating systems. The key to all of these tools is data and the use of data (Carlos, 2017).

Today, the most important aspect of terminal management when it comes to improvement is the storage and management of containers. This process is made easier and more efficient by having information at the terminal operator’s disposal, so that in turn they know what to do and when to do it. Data collection allows the terminal to create a container stacking plan. Knowing when a container will need to be moved and where it is going next will determine how it is stored. It would not be ideal to house containers in a formation that will cause multiple containers to be moved just to access one container. This method is inefficient because it creates more work, and it causes delays (Mazloumi, 2021). The use of data needs to not only create a more informed terminal management team, but it needs to create some connectivity and integration of the various cargo-handling equipment. This equipment includes straddle carriers, yard cranes, quay cranes, and container transportation vehicles (Mazloumi, 2021). Real-time data can assist in the planning of ship docking and the loading and unloading of cargo. The ability of terminal planners to know when a ship will arrive allows them to schedule the availability of cranes and for that equipment to be staffed. Even knowing when the terminal will experience the most congestion will allow the operators to know what equipment should be utilized during that time. This is crucial because use of the wrong equipment could cause further congestion and gridlock (Mazloumi, 2021).

The first aspect of incorporating data is cargo tracking. Currently, most ports are not equipped with the technology needed to provide precise tracking comparable to that used in domestic consumer shipping. The port of Houston has an online container tracking system. The Terminal Toolbox allows customers to track their containers and gain access to berth applications and safety manuals. Cargo tracking is important because of the over 1,600 containers that are lost at sea each year. But tracking cargo also improves the customer service aspect of terminal management.

Ports process very large volumes of containers each year. But with the large number of containers comes numerous customers. These customers are seeking data. They need data about the location and condition of cargo. While location tracking can tell the customer where the cargo is, condition tracking can let the customer know whether the cargo is damaged or at risk of becoming damaged. Container cargo can be damaged by vandalism, theft, or condensation. Also, refrigerated cargo is subject to strict temperature controls. If the refrigeration unit is not operational, it can affect the condition of the cargo, especially for medicines and perishable goods (food). Getting cargo from the customer to its destination undamaged is important and affects the relationships between the port, the customer, the carrier, and other third parties involved in the shipment.

If a certain port or carrier has a tendency to deliver cargo to its destination damaged, these parties are less likely to utilize these parties in the future. It could also affect their liability for the lost or damaged cargo, which will cost the port money in attorney fees, money judgments, and increased insurance costs. Another way data can assist in improving terminal management is increasing the ability to predict repair needs. If data is available to anticipate required maintenance and prevent delays, it will improve efficiency. The final data-driven tool for improving terminal management is the acquisition and use of terminal operating systems. Many terminals used to rely on pen and paper to track production. With the use of post-Panamax ships and increased capacity, this antiquated method is simply inefficient.

Today, terminal operating systems help to track productivity and issues as they happen. These systems give information and analysis quickly to allow the prevention of bottleneck situations and to allow for the deployment of new equipment if needed (Carlos, 2017). These data-related solutions will help to solve efficiency issues. But they will not necessarily assist with the more ancillary issues that arise with terminal management. Increased information and data will not likely solve truck congestion in nearby communities. Although it will help regulate when trucks proceed to the terminal and how long they spend in and around these port facilities. More data will not solve the issue of pollution. This is because data does not wholly eliminate the presence of pollution causing vehicles and their effects. Technology and data can help to measure pollutants and determine the best way to deal with the issue by giving guidance to law makers and others.

Overall, the global transportation system will improve with better technology, data, and the sharing of information. This sharing of information will facilitate better shipment predictability, alleviate potential gridlock and stalls, assist in the movement and storage of containers, assist fluidity in intermodal transport, and provide a better experience for all parties from customers to port managers to carriers.

Carlos, Guille. (May 14, 2017). Harnessing data to boost terminal management. The Maritime Executive. Retrieved April 18, 2022, from https://www.maritimeexecutive.com/blog/harnessing-data-to-boost-terminal-management

Mazloumi, Medhi & Hassel, Edwin van. Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach. Retrieved April 18, 2022, from https://www.mdpi.com/2071-1050/13/17/9702

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